Statistical condition monitoring based on vibration signals

Zhang, Sheng, Mathew, Joseph, Ma, Lin, Sun, Yong, & Mathew, Avin D. (2004) Statistical condition monitoring based on vibration signals. In Vyas, N. S., Rao, J. S., Mathew, Joseph, Ma, Lin, & Raghuram, V. (Eds.) VETOMAC-3 & ACSIM-2004, 6-9 December 2004, New Delhi, India.


Designing control limits for condition monitoring is an important aspect of setting maintenance schedules and has been virtually ignored by researchers to date. This paper proposes a novel statistical process control tool, the Weighted Loss function CUSUM (WLC) chart, for the detection of condition variation. The control limit was designed using baseline condition data, where the process was fitted by an autoregressive model and the residuals were used as the chart statistic. The condition variation is reflected by the changes of mean and variance of the statistic’s distribution against baseline condition, which can be detected by a single WLC chart. The approach was evaluated using a case study which showed that the chart can detect faulty conditions as well as their severity. The proposed approach has the advantage of requiring healthy baseline data only for the design of condition classifiers. It is applicable in numerous practical situations where data from faulty conditions are unavailable.

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ID Code: 13310
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Mechanical Engineering not elsewhere classified (091399)
Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)
Divisions: Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2004 (The authors)
Deposited On: 16 Apr 2008 00:00
Last Modified: 29 Feb 2012 13:05

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